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# rapids-singlecell: GPU-Accelerated Single-Cell Analysis within scverse®

rapids-singlecell provides GPU-accelerated single-cell analysis with an AnnData-first API.
It is largely compatible with Scanpy and includes selected functionality from Squidpy, decoupler, and pertpy.
Computations use CuPy and NVIDIA RAPIDS for performance on large datasets.

- **GPU acceleration**: Common single-cell workflows on `AnnData` run on the GPU.
- **Ecosystem compatibility**: Works with Scanpy APIs; includes pieces from Squidpy, decoupler, and pertpy.
- **Simple installation**: Available via Conda and PyPI.

## Documentation

For more information please have a look through the [documentation](https://rapids-singlecell.readthedocs.io/en/latest/)

## Citation

If you use this code, please cite: [![DOI](https://zenodo.org/badge/364573913.svg)](https://zenodo.org/badge/latestdoi/364573913)

Please also consider citing: [rapids-single-cell-examples](https://zenodo.org/badge/latestdoi/265649968) and  [scanpy](https://doi.org/10.1186/s13059-017-1382-0)

In addition to that please cite the methods' original research articles in the [scanpy documentation](https://scanpy.readthedocs.io/en/latest/references.html)

Please cite the relevant tools if used: [decoupler](https://doi.org/10.1093/bioadv/vbac016) for decoupler functions, [squidpy](https://doi.org/10.1038/s41592-021-01358-2) for spatial analysis, and [pertpy](https://doi.org/10.1038/s41592-024-02233-6) for perturbation analysis.

[//]: # (numfocus-fiscal-sponsor-attribution)

rapids-singlecell is part of the scverse® project ([website](https://scverse.org), [governance](https://scverse.org/about/roles)) and is fiscally sponsored by [NumFOCUS](https://numfocus.org/).
If you like scverse® and want to support our mission, please consider making a tax-deductible [donation](https://numfocus.org/donate-to-scverse) to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

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